The influence of minimum wage regulation on labor income share and overwork: evidence from China

Figures & data

Table 1. Definition of variables and statistical description of sample 1: inter-provincial data of all industries.

Variable	Variable Name	Formula	Sample Size	Mean	Std. Dev.	Min	Max
Labor income share	ls	LI/GDP	771	0.492	0.074	0.314	0.816
Wage rate	w	ASUE	771	1.759	2.255	0.051	13.499
The proportion of the first industry	gdp1r	AVFI/GDP	771	0.149	0.083	0.004	0.460
The proportion of the second industry	gdp2r	AVSI/GDP	771	0.442	0.083	0.171	0.594
GDP per capita	gdppc	GDPPC	771	2.362	2.341	0.123	12.899
Indirect tax	tr	NPT/GDP	771	0.141	0.032	−0.003	0.266
The proportion of foreign capital	fcr	RCFE/GDP	770	3.875	4.951	0.077	57.387
Foreign trade dependency	ftdpd	TIE/GDP	771	0.386	0.450	0.000	2.327
Sex ratio	sr	SR	465	104.099	3.774	92.250	120.430
Dependency ratio	dpdr	TDR	465	37.348	6.763	19.300	57.600

Source: China Statistical Yearbook.

Notes: 1. LI-labor income (100 million yuan per year); GDP-gross domestic product (100 million yuan per year); ASUE-average salary of urban employees (10 thousand yuan per year); AVFI-added value of the first industry (100 million yuan per year); AVSI-added value of the second industry (100 million yuan per year); GDPPC-GDP Per capita (10 thousand yuan per year); NPT-net production tax (100 million yuan per year); RCFE-registered capital of foreign enterprises (million dollars per year); TIE-total import and export (10 million dollars per year); SR-sex ratio (the female population = 100); TDR-total dependency ratio (Population = 100).

2. The principle of data processing is to make the numeric value of each variable as close as possible through the unit adjustment, and the coefficient results after regressions would be relatively close. Some uncommon units of measurement are used, such as 100 million, 10 thousand and million yuan, et al.

Table 2. Definition of variables and statistical description of sample 2: inter-provincial data of industry only.

Variable	Variable Name	Formula	Sample Size	Mean	Std. Dev.	Min	Max
Labor income share	ls	LI/VAI	372	0.108	0.045	0.043	0.268
Wage rate	w	ASUEI	372	4.431	1.789	1.485	11.170
Indirect tax	tr	VATI/VAI	279	0.117	0.021	0.073	0.173
The proportion of foreign capital	fcr	FCI/PICI	341	0.095	0.089	0.002	0.401
The proportion of state-owned capital	stater	SCI/PICI	341	0.257	0.133	0.036	0.739
Export dependency	exdpd	EX/TOI	341	0.293	0.347	0.000	1.499
Capital-labor ratio	kl	FA/EN	279	67.259	33.774	18.857	248.761
Sex ratio	sr	SR	341	104.315	3.831	94.650	120.430
Dependency ratio	dpdr	TDR	341	36.321	6.460	19.300	55.100

Source: China Statistical Yearbook.

Notes: 1. China statistical yearbook includes three sub-sectors of industry, which are ‘mining’, ‘manufacturing’ and ‘electric power, steam and water industry’.

2. LI-total labor income of industry (100 million yuan per year); VAI-added value of industry (100 million yuan per year); ASUEI-the weighted average wage rate of industry. Wage rate is the average wage of urban employees (10 thousand yuan per year), and the weight is labor income share from each sub-sector; VATI-value added tax of industry (100 million yuan per year); FCI-foreign capital of industry (100 million yuan per year); PICI-paid-in capital of industry (100 million yuan per year); SCI-state owned capital of industry (100 million yuan per year); EX-export volume (100 million yuan per year); TOI-total output of industry (100 million yuan per year); FA-fixed assets (100 million yuan per year); EN-the employment of mining, manufacturing and electric power, steam and water industry together (10 thousand persons); SR-sex ratio (the female population = 100); TDR-total dependency ratio (the population = 100).

Table 3. Definition of variables and statistical description of sample 3: industrial enterprise data.

Variable	Variable Name	Formula	Sample Size	Mean	Std. Dev.	Min	Max
Labor income share	ls	TW/VAI	2435670	0.316	0.226	0	1
Wage rate	w	TW/EN	2733774	19.554	56.122	0	2034
Production tax	tr	TAX/VAI	2435670	0.183	0.170	−3.067	4.715
The proportion of foreign capital	fcr	FC/PIC	2374755	0.073	0.242	0	1
The proportion of capital from Hong Kong, Macau and Taiwan investment	hmtr	CHMT/PIC	2371745	0.075	0.246	0	1
The proportion of state-owned capital	stater	SC/PIC	2374717	0.110	0.300	0	1
Export dependency	exdpd	EX/VAI	2170793	0.143	0.307	0	1.300
Capital-labor ratio	kl	FA/EN	2724113	126.662	429.402	0	11254
Monopoly pricing power	markup	RCMB/CMB	2750613	0.160	0.130	−0.875	0.975
Financing constraints	Loanrate	IE/LIA	2654771	0.041	0.155	−0.100	4.51

Source: China’s Industrial Enterprise Database.

Notes: TW-total wage (million yuan per year); VAI-added value of industry (million yuan per year); EN-the number of employees (thousand persons); TAX-’taxes and extra charges of main business’ + VAT + ‘taxes in management expenses’ (million yuan per year); FC-foreign capital (million yuan per year); PIC-paid-in capital (million yuan per year); CHMT-capital from Hong Kong, Macau and Taiwan (million yuan per year); SC-state owned capital (million yuan per year); EX-export volume (million yuan per year); FA-fixed assets (million yuan per year); EN-the number of employees (thousand persons); RCMB-revenue and cost of main business (million yuan per year); CMB-cost of main business (million yuan per year); IE-interest expenditure (million yuan per year); LIA-liability (million yuan per year).

Table 4. Regression results.

Variable	Regression 1: sample1			Regression 2: sample 2			Regression 3: sample 3
	Uni-variate	Fixed	Random	Uni-variate	Fixed	Random	Uni-variate	Fixed	Random
W	0.005*** (0.001)	0.012*** (0.003)	0.013*** (0.002)	0.010*** (0.001)	0.023*** (0.003)	0.022*** (0.003)	0.00033*** (0.00000)	0.00062*** (0.00000)	0.00067*** (0.00000)
gdp1r		0.237* (0.138)	0.238** (0.094)
gdp2r		−0.179*** (0.060)	−0.188*** (0.045)
gdppc		−0.007** (0.003)	−0.008*** (0.002)		−0.007*** (0.003)	−0.005** (0.002)
tr		−0.556*** (0.116)	−0.572*** (0.101)		0.123 (0.081)	0.141** (0.077)		0.26832*** (0.00099)	0.23402*** (0.00086)
fcr		−0.003 (0.002)	−0.003** (0.001)		−0.064 (0.069)	−0.002 (0.051)		−0.00368*** (0.00141)	0.04616*** (0.00086)
hmtr								−0.00628*** (0.00136)	0.06356*** (0.00084)
stater					0.055*** (0.017)	0.069*** (0.016)		0.02495*** (0.00098)	0.08909*** (0.00066)
ftdpd		−0.029* (0.016)	0.0005 (0.011)
exdpd					0.002 (0.015)	0.016 (0.013)		0.02003*** (0.00095)	0.09160*** (0.00066)
sr		0.0005 (0.001)	0.001 (0.001)		0.000 (0.000)	0.000 (0.000)
dpdr		−0.0009 (0.001)	0.0002 (0.001)		0.000 (0.000)	0.000 (0.000)
kl					−0.001*** (0.000)	−0.001*** (0.000)		−0.00007*** (0.00000)	−0.00008*** (0.00000)
markup								−0.16584*** (0.00163)	−0.14712*** (0.00127)
loan rate								−0.02612*** (0.00128)	−0.07060*** (0.00108)
cons.	0.505*** (0.003)	0.591*** (0.097)	0.488*** (0.076)	0.064*** (0.003)	0.024 (0.030)	0.002 (0.028)	0.30979*** (0.00012)	0.27761*** (0.00042)	0.26408*** (0.00037)
sample size	771	465	465	372	197	197	2412377	1980611	1980611
R^2	0.0385	0.5774	0.7230	0.5346	0.3626	0.5852	0.0053	0.0443	0.1174

Notes: ***, ** and * refer to statistically significance at the levels of 1%, 5% and 10%. The data in brackets indicate robust standard errors of heteroscedasticity.

Table 5. Robust test results.

Variable	Regression 4: Reducing variables of sample 1		Regression 5: Taking the logarithm of sample 3			Regression 6: Selecting a sub-sample of sample 3 by year
	Fixed	Random	Uni-variate	Fixed	Random	2001	2007	2013
W	0.016*** (0.002)	0.014*** (0.002)	0.245*** (0.001)	0.313*** (0.063)	0.278*** (0.040)	0.00137*** (0.00004)	0.00202*** (0.00002)	0.00038*** (0.00001)
gdp1r	0.724*** (0.054)	0.645*** (0.048)
gdp2r	−0.120*** (0.041)	−0.142*** (0.037)
Gdppc	−0.009*** (0.002)	−0.008*** (0.002)
Tr	−0.435*** (0.087)	−0.487*** (0.080)		0.171*** (0.027)	0.163*** (0.021)	−0.16554*** (0.00277)	0.27643*** (0.00235)	−0.38104*** (0.00491)
fcr	−0.001*** (0.000)	−0.001** (0.000)		0.028*** (0.034)	−0.016*** (0.020)	−0.04097*** (0.00283)	0.01938*** (0.00150)	0.04825*** (0.00306)
hmtr				−0.006*** (0.034)	−0.026*** (0.019)	0.01544*** (0.00250)	0.08956*** (0.00150)	0.10418*** (0.00331)
stater				0.040*** (0.036)	0.053*** (0.022)	0.13818*** (0.00156)	0.08840*** (0.00202)	0.10145*** (0.00469)
ftdpd	−0.007 (0.009)	0.006 (0.008)
exdpd				−0.002*** (0.027)	0.051*** (0.016)	0.09962*** (0.00197)	0.15174*** (0.00125)	0.16037*** (0.00296)
sr
dpdr
kl				−0.196*** (0.072)	−0.299*** (0.031)	−0.00016*** (0.00000)	−0.00009*** (0.00000)	−0.00010*** (0.00000)
markup				−0.150*** (0.055)	−0.154*** (0.037)	−0.34064*** (0.00422)	−0.11751*** (0.00276)	−0.42281*** (0.00656)
loan rate				−0.002*** (0.030)	0.009*** (0.022)	−0.20047*** (0.00485)	−0.10591*** (0.00255)	−0.14652*** (0.00413)
cons.	0.482*** (0.027)	0.509*** (0.025)	−2.055*** (0.002)	−1.250*** (0.367)	−0.644*** (0.201)	0.47057*** (0.00131)	0.18720*** (0.00076)	0.51157*** (0.00168)
Sample size	770	770	2386941	687	687	140858	311704	80106
R^2	0.6958	0.7183	0.0349	0.1811	0.2908	0.1665	0.1556	0.2501

Notes: ***, ** and * refer to statistically significance at the levels of 1%, 5% and 10%. The data in brackets indicate robust standard errors of heteroscedasticity.

Table 6. Definition of variables and statistical description of sample 4.

Variable	Variable Name	Formula	Sample Size	Mean	Std. Dev	Min	Max
Weekly working hours	hourwk	Weekly working hours	1286	40.078	4.016	24	63
Overwork ratio	hour48shr	The proportion of workers working over 48 hours per week	1074	14.717	12.339	0.79	94.44
Wage rate	w	Wage (thousand USD per month)	750	2.391	17.981	0.00004	359.1
Male worker ratio	sex	Male workers divided by the total employment	1274	0.578	0.07	0.47346	0.93
Employment rate	empl	The quantity of employment divided by population	1274	60.816	9.732	33.45	93.32
Mandatory minimum wage	mwr	Minimum wage according to law or labor union (USD)	632	648.757	619.97	2.32	2721
The Gini coefficient	gini	The Gini coefficient times 100	895	41.683	9.34	22	77
GDP per capita	gdppc	GDP per capita (USD)	910	26.387	17.3	0.594	98.95
Income groups	incgrp	Income is divided into four groups, from low to high	913	3.507	0.736	1	4
Labor dependency ratio	depend	(the quantity of unemployed above the age of 15 + children under the age of 14) / the quantity of employment	1274	1.381	0.502	0.33	4.5
Chinese culture or not	culture	The dummy variable, Chinese culture is marked as 1, otherwise is 0	1286	0.033	0.18	0	1
The proportion of professional positions	prof	The proportion of professional positions	1274	13.93	6.62	0.35	41.3
The proportion of operational positions	mach	The proportion of machine operational positions	1274	10.873	5.037	0.25	23.28

Source: www.ilo.org. The Gini coefficients are from the World Income Inequality Database (www.wider.unu.edu/project/wild-world- income- inequality-database).

Figure 1. Weekly working hours among different countries.

Note: The data of other economies are generally in the middle area of Figure 1.²

Table 7. Regression results of sample 4.

Variable	Regression 7: sample 4, hourwk as the explained variable			Regression 8: sample 4, hour48shr as the explained variable
	Uni-variate	Fixed	Random	Uni-variate	Fixed	Random
w	0.0014(0.00405)	−0.166(0.318)	−0.193(0.306)	0.014(0.009)	0.595(0.639)	0.345(0.642)
sex		17.298***(7.747)	21.962***(5.29)		28.993*(15.68)	30.022**(12.776)
empl		0.161(0.085)	0.059(0.061)		−0.329(0.200)	0.443***(0.150)
mwr		0.001(0.001)	−0.001(0.001)		−0.002(0.002)	−0.001(0.002)
gini		0.005(0.009)	0.006(0.008)		−0.052***(0.018)	−0.035*(0.018)
gdppc		−0.020(0.028)	−0.025(0.025)		−0.126**(0.056)	−0.090*(0.052)
incgrp		(omitted)	2.407***(0.717)		(omitted)	−3.166*(1.749)
depend		3.702**(1.64)	2.141*(1.146)		−4.846(3.678)	8.454***(2.755)
culture		(omitted)	5.944*(3.261)		(omitted)	(omitted)
prof		−0.103**(0.050)	−0.096**(0.047)		−0.265**(0.103)	−0.213**(0.101)
mach		0.202***(0.058)	0.217***(0.055)		0.265**(0.126)	0.126(0.121)
Constant term	40.34***(0.059)	15.475*(9.086)	11.938(7.720)	16***(0.138)	25.976(19.973)	−24.280(19.545)
Sample size	750	332	332	647	304	304
R^2	0.0002	0.3715	0.3658	0.0044	0.3320	0.2900

Notes: ***, ** and * refer to significant influence at the statistical levels of 1%, 5% and 10%. The data in brackets indicate robust standard errors of heteroscedasticity.